rekriz11/MultiVENT2.0

Dataset Card for MultiVENT 2.0

This dataset card provides details about MultiVENT 2.0, a large-scale, multi-lingual event-centric video retrieval benchmark featuring a collection of more than 218,000 news videos and over 3,900 queries targeting specific world events.

Dataset Details

Dataset Description

MultiVENT 2.0 consists over 218,000 videos, with 108,500 videos for training (MultiVENT Train) and 109,800 for testing MultiVENT Test.

The collection contains all 2,400 videos from original MultiVENT dataset, a carefully curated set of Multilingual Videos of Events with aligned Natural Text, augmented with a subset of videos from Internvid, a corpus containing more than seven million YouTube videos and over 760,000 hours of content.

• Created by: The Human Language Technology Center of Excellence and Johns Hopkins University
• Language(s) (NLP): Arabic, Chinese, English, Korean, Russian, Spanish
• License: apache-2.0

Dataset Sources [optional]

• Repository: https://github.com/katesanders9/multiVENT
• Paper [optional]: https://arxiv.org/abs/2410.11619
• Workshop on Multimodal Augmented Generation via Multimodal Retreival (MAGMaR): https://nlp.jhu.edu/magmar/

Uses

Direct Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

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Annotations [optional]

Annotation process

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

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Citation [optional]

BibTeX:

@misc{kriz2025multivent20massivemultilingual, title={MultiVENT 2.0: A Massive Multilingual Benchmark for Event-Centric Video Retrieval}, author={Reno Kriz and Kate Sanders and David Etter and Kenton Murray and Cameron Carpenter and Kelly Van Ochten and Hannah Recknor and Jimena Guallar-Blasco and Alexander Martin and Ronald Colaianni and Nolan King and Eugene Yang and Benjamin Van Durme}, year={2025}, eprint={2410.11619}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2410.11619}, }

@misc{sanders2023multiventmultilingualvideosevents, title={MultiVENT: Multilingual Videos of Events with Aligned Natural Text}, author={Kate Sanders and David Etter and Reno Kriz and Benjamin Van Durme}, year={2023}, eprint={2307.03153}, archivePrefix={arXiv}, primaryClass={cs.IR}, url={https://arxiv.org/abs/2307.03153}, }

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